An Energy Efficient Cluster Head Selection with Optimal Path Selection Approach in Wireless Sensor Networks

Distribution of independent sensors can be termed as a Wireless Sensor Network (WSN) as it monitors the environmental or physical circumstances like pressure, vibration, sound, temperature and so on cooperatively. WSNs usually consumes less energy and has extremely long lifetime for network which are considered to be critical tasks, particularly in sensor networks involving of nodes which are observed to be lightweight and consumes constricted energy source. The Hybrid Energy-Efficient Multi-Path (HEEMP) routing is the preceding scheme modeled for wireless sensor networks. On the other hand, an appropriate selection methodology for CH possessing ideal skills is essential to stabilize the load of network lifetime and network’s energy-efficiency. Here the cost of energy needed to choose a path for forwarding of data is alone taken into account. Besides, it doesn’t learn about the quality of link to progress the ratio of packet delivery. So as to resolve this issue, the projected scheme modeled a Dynamic Binomial Distribution centered Glowworm Swarm Optimization algorithm along with Improved Link Quality Cost Function based data forwarding (DBD-GSO with ILQCF) methods. In the projected work of study, selection of Cluster Head (CH) is donebased on the transmission power, residual energy, node degree and minimum distance with the assistance of Dynamic Binomial Distribution based Glowworm Swarm Optimization algorithm (DBD-GSO). In order to exchange information with the cluster head inside the clusters, the nodes implement multi-hop routing technique. This technique after receiving of data packets from every member of cluster it transfers the data aggregated on the pre calculated track to the sink. The ideal path is selected in a way that the overall consumption of energy in the routing path is the least with high link quality and it is done by employing Improved Link Quality Cost Function (ILQCF). All the tests are carried by utilizing a simulator called NS-2. The projected and existing methods for detection are contrasted by means of features like throughput, end to end delay and consumption of total energy.